AI Agents Requirements

What AI Agents Need to Be Successful

Date: January 2026 Purpose: Detailed analysis of what AI agents need from OASIS infrastructure and what additional capabilities must be built

Executive Summary

AI agents need 10 core capabilities to operate successfully in a multi-agent system. OASIS already provides 6 of these through existing infrastructure. We need to build 4 new layers specifically for agent orchestration.

Current OASIS Coverage: 60% Gap to Fill: 40% (Agent-specific orchestration layer)

Part 1: What AI Agents Need (The 10 Core Requirements)

1. Identity & Discovery 🔑

What Agents Need:

Unique agent identity (like user accounts)
Capability registry (what can this agent do?)
Discovery mechanism (find agents by capability)
Agent metadata (version, status, performance)

Current OASIS: ✅ 80% Complete

Avatar System provides identity
Provider registry exists (can extend for agents)
Missing: Agent capability matching, agent discovery API

2. Communication & Messaging 💬

What Agents Need:

Direct agent-to-agent messaging
Broadcast/event system for announcements
Message queuing for async communication
Message routing (send to agent by capability)

Current OASIS: ✅ 70% Complete

MESSAGING API exists (avatar-to-avatar)
ONET network provides broadcasting
Missing: Agent-specific message routing, agent message queues

3. Shared State & Memory 🧠

What Agents Need:

Shared knowledge base (what agents know)
Agent memory persistence
State synchronization across agents
Conflict resolution for shared data

Current OASIS: ✅ 90% Complete

Holon system provides shared state
HyperDrive handles synchronization
Consensus engine resolves conflicts
Missing: Agent-specific memory schemas

4. Task Delegation & Routing 📋

What Agents Need:

Task queue system
Capability-based task routing
Task assignment and tracking
Task result aggregation

Current OASIS: ⚠️ 30% Complete

HyperDrive routes to providers (similar concept)
Missing: Task queue API, task routing engine, task tracking

5. Resource Management 💻

What Agents Need:

Compute resource allocation
Storage quotas per agent
Rate limiting and quotas
Cost tracking per agent

Current OASIS: ✅ 60% Complete

Provider system manages resources
Missing: Agent-specific quotas, agent cost tracking

6. Security & Permissions 🔒

What Agents Need:

Agent authentication
Permission system (what agents can do)
API key management per agent
Rate limiting per agent

Current OASIS: ✅ 80% Complete

Avatar system provides authentication
KEYS API manages cryptographic keys
Missing: Agent-specific permissions, agent API keys

7. Observability & Debugging 🔍

What Agents Need:

Agent execution logs
Agent performance metrics
Agent error tracking
Agent activity dashboard

Current OASIS: ✅ 70% Complete

STATS API provides metrics
Blockchain provides audit trail
Missing: Agent-specific logs, agent debugging tools

8. Consensus & Coordination 🤝

What Agents Need:

Multi-agent decision making
Consensus algorithms for agent groups
Conflict resolution between agents
Agent voting/agreement mechanisms

Current OASIS: ✅ 85% Complete

HyperDrive consensus engine exists
Oracle system handles multi-source consensus
Missing: Agent-specific consensus protocols

9. Persistence & Reliability 💾

What Agents Need:

Agent state persistence
Agent recovery after failure
Agent state backup
Cross-chain agent state

Current OASIS: ✅ 95% Complete

Multi-provider persistence (MongoDB, IPFS, blockchains)
Auto-failover ensures reliability
Missing: Agent-specific recovery mechanisms

10. Workflow Orchestration 🔄

What Agents Need:

Multi-step task workflows
Agent pipeline orchestration
Conditional routing (if agent A fails, try agent B)
Workflow state management

Current OASIS: ⚠️ 20% Complete

HyperDrive provides basic routing
Missing: Workflow engine, pipeline orchestration, conditional logic

Part 2: What OASIS Already Provides (The Foundation)

✅ Already Built - Ready to Use:

1. Identity System (Avatar API)

// Agents can register as Avatars
POST /api/avatar/register
{
  "username": "agent_001",
  "avatarType": "AI_Agent",
  "metadata": {
    "capabilities": ["image_generation", "text_analysis"],
    "model": "gpt-4",
    "version": "1.0"
  }
}

What This Gives Agents:

Unique identity across all systems
Authentication and authorization
Profile management
Cross-chain identity

2. Communication (MESSAGING API)

// Agents can message each other
POST /api/messaging/send-message
{
  "fromAvatarId": "agent_001",
  "toAvatarId": "agent_002",
  "message": "Can you process this image?",
  "metadata": {
    "taskId": "task_123",
    "priority": "high"
  }
}

What This Gives Agents:

Direct agent-to-agent communication
Message history
Notification system
Cross-chain messaging

3. Shared State (Holon System)

// Agents can share knowledge
POST /api/data/save-holon
{
  "name": "agent_knowledge_base",
  "holonType": "AgentMemory",
  "metadata": {
    "agentId": "agent_001",
    "knowledge": {...},
    "timestamp": "2026-01-15T10:00:00Z"
  }
}

What This Gives Agents:

Shared memory across agents
Persistent state storage
Multi-provider backup
Conflict resolution

4. Resource Management (Provider System)

// Agents can use any provider
GET /api/provider/health
// Returns: Available compute/storage resources

POST /api/data/save-holon
// Automatically routes to best provider

What This Gives Agents:

Access to 50+ providers
Auto-failover if provider fails
Load balancing
Cost optimization

5. Consensus Engine (HyperDrive)

// Multi-agent decisions
// HyperDrive consensus engine aggregates results
// from multiple agents/providers

What This Gives Agents:

Multi-agent consensus
Conflict resolution
Weighted decision making
Reliability through redundancy

6. Observability (STATS API)

// Agent performance tracking
GET /api/stats/avatar/{agentId}
// Returns: Performance metrics, activity logs

What This Gives Agents:

Performance metrics
Activity tracking
Error monitoring
Usage statistics

Part 3: What We Need to Build (The Agent Layer)

🚧 New Capabilities Required:

1. Agent Registry & Discovery System ⭐ HIGH PRIORITY

What It Does:

Register agents with their capabilities
Discover agents by capability/requirement
Match tasks to agents
Track agent availability

API Design:

// Register agent with capabilities
POST /api/agents/register
{
  "agentId": "agent_001",
  "name": "Image Generation Agent",
  "capabilities": [
    {
      "type": "image_generation",
      "models": ["dall-e-3", "midjourney"],
      "maxResolution": "4096x4096",
      "costPerRequest": 0.02
    },
    {
      "type": "image_analysis",
      "models": ["gpt-4-vision"],
      "maxImages": 10
    }
  ],
  "endpoints": {
    "api": "https://agent-001.example.com/api",
    "webhook": "https://agent-001.example.com/webhook"
  },
  "availability": "online",
  "maxConcurrentTasks": 10
}

// Discover agents by capability
GET /api/agents/discover?capability=image_generation&available=true
// Returns: List of agents that can generate images

// Get agent details
GET /api/agents/{agentId}
// Returns: Full agent profile, capabilities, status

Implementation:

Extend Avatar API for agent-specific fields
Create AgentCapability Holon type
Build discovery search index
Add agent health monitoring

Timeline: 4-6 weeks

2. Task Queue & Workflow Engine ⭐ HIGH PRIORITY

What It Does:

Queue tasks for agents
Route tasks to appropriate agents
Track task status and results
Orchestrate multi-step workflows

API Design:

// Submit task to queue
POST /api/agents/tasks/submit
{
  "taskId": "task_123",
  "type": "image_generation",
  "requirements": {
    "capability": "image_generation",
    "model": "dall-e-3",
    "resolution": "2048x2048"
  },
  "input": {
    "prompt": "A futuristic cityscape",
    "style": "cyberpunk"
  },
  "priority": "high",
  "deadline": "2026-01-15T12:00:00Z",
  "callback": "https://myapp.com/webhook/task-complete"
}

// Task routing (automatic)
// OASIS finds agent with matching capability
// Routes task to best available agent
// Tracks task status

// Get task status
GET /api/agents/tasks/{taskId}
// Returns: Status, assigned agent, progress, result

// Multi-step workflow
POST /api/agents/workflows/create
{
  "workflowId": "workflow_001",
  "steps": [
    {
      "stepId": "step_1",
      "type": "text_analysis",
      "input": "{{input.text}}",
      "onSuccess": "step_2",
      "onFailure": "step_error"
    },
    {
      "stepId": "step_2",
      "type": "image_generation",
      "input": "{{step_1.result.summary}}",
      "onSuccess": "step_3"
    },
    {
      "stepId": "step_3",
      "type": "image_analysis",
      "input": "{{step_2.result.imageUrl}}",
      "onSuccess": "complete"
    }
  ]
}

Implementation:

Build task queue system (Redis/RabbitMQ backend)
Create task routing engine
Build workflow state machine
Add task result aggregation

Timeline: 6-8 weeks

3. Agent Communication Protocol ⭐ MEDIUM PRIORITY

What It Does:

Standardized agent-to-agent communication
Agent message routing by capability
Agent event broadcasting
Agent collaboration protocols

API Design:

// Send message to agent (by capability)
POST /api/agents/messages/send-by-capability
{
  "capability": "image_generation",
  "message": {
    "type": "task_request",
    "taskId": "task_123",
    "input": {...}
  },
  "routing": {
    "strategy": "first_available", // or "best_match", "load_balanced"
    "timeout": 30
  }
}

// Agent event broadcasting
POST /api/agents/events/broadcast
{
  "event": "task_completed",
  "agentId": "agent_001",
  "data": {
    "taskId": "task_123",
    "result": {...}
  },
  "subscribers": ["agent_002", "agent_003"] // or "all"
}

// Agent collaboration protocol
POST /api/agents/collaborate
{
  "taskId": "task_123",
  "agents": ["agent_001", "agent_002", "agent_003"],
  "protocol": "consensus", // or "voting", "delegation"
  "input": {...}
}

Implementation:

Extend MESSAGING API for agent routing
Build agent event system
Create collaboration protocols
Add agent message queuing

Timeline: 4-6 weeks

4. Agent Monitoring & Debugging Dashboard ⭐ MEDIUM PRIORITY

What It Does:

Real-time agent status monitoring
Agent performance analytics
Agent error tracking and debugging
Agent cost tracking

API Design:

// Get agent status
GET /api/agents/{agentId}/status
// Returns: Online/offline, current tasks, performance metrics

// Get agent performance
GET /api/agents/{agentId}/performance
// Returns: Tasks completed, success rate, avg response time, cost

// Get agent logs
GET /api/agents/{agentId}/logs?startTime=...&endTime=...
// Returns: Execution logs, errors, debug info

// Agent debugging
POST /api/agents/{agentId}/debug
{
  "taskId": "task_123",
  "action": "trace", // or "replay", "inspect"
  "options": {
    "includeState": true,
    "includeMessages": true
  }
}

Implementation:

Build agent monitoring service
Create logging aggregation
Build debugging tools
Create dashboard UI

Timeline: 6-8 weeks

Part 4: Implementation Roadmap

Phase 1: Foundation (Weeks 1-6) ⭐ CRITICAL

Goal: Enable basic agent registration and discovery

Tasks:

Agent Registry API (2 weeks)
- Extend Avatar API for agent registration
- Create AgentCapability Holon schema
- Build agent metadata storage
Agent Discovery (2 weeks)
- Build capability search index
- Create discovery API endpoints
- Add agent health monitoring
Basic Task Queue (2 weeks)
- Simple task submission API
- Task routing to agents
- Task status tracking

Deliverable: Agents can register, be discovered, and receive tasks

Phase 2: Communication (Weeks 7-12) ⭐ HIGH PRIORITY

Goal: Enable agent-to-agent communication and collaboration

Tasks:

Agent Messaging (3 weeks)
- Extend MESSAGING API for agents
- Build capability-based routing
- Add message queuing
Agent Events (2 weeks)
- Event broadcasting system
- Agent subscriptions
- Event history
Agent Collaboration (3 weeks)
- Multi-agent protocols
- Consensus mechanisms
- Result aggregation

Deliverable: Agents can communicate and collaborate

Phase 3: Orchestration (Weeks 13-18) ⭐ HIGH PRIORITY

Goal: Enable complex workflows and task orchestration

Tasks:

Workflow Engine (4 weeks)
- Workflow definition language
- State machine execution
- Conditional routing
Task Management (2 weeks)
- Advanced task queuing
- Task prioritization
- Task scheduling

Deliverable: Complex multi-agent workflows work end-to-end

Phase 4: Observability (Weeks 19-24) ⭐ MEDIUM PRIORITY

Goal: Full visibility into agent operations

Tasks:

Monitoring System (3 weeks)
- Real-time agent status
- Performance metrics
- Health checks
Debugging Tools (3 weeks)
- Agent execution logs
- Error tracking
- Debug dashboard

Deliverable: Complete observability into agent fleet

Part 5: Technical Architecture

Agent Layer Architecture

┌─────────────────────────────────────────────────────────┐
│              Agent Orchestration Layer                  │
│  (NEW - What We Need to Build)                         │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  ┌──────────────┐  ┌──────────────┐  ┌─────────────┐ │
│  │ Agent        │  │ Task Queue   │  │ Workflow    │ │
│  │ Registry     │  │ Engine       │  │ Engine       │ │
│  └──────┬───────┘  └──────┬───────┘  └──────┬──────┘ │
│         │                  │                  │         │
│         └──────────────────┼──────────────────┘         │
│                            │                            │
│  ┌─────────────────────────┼──────────────────────────┐ │
│  │      Agent Communication Layer                       │ │
│  │  (Extends MESSAGING API)                             │ │
│  └─────────────────────────┼──────────────────────────┘ │
│                            │                            │
└────────────────────────────┼────────────────────────────┘
                             │
                             ▼
┌─────────────────────────────────────────────────────────┐
│         Existing OASIS Infrastructure                 │
│  (Already Built - Foundation)                          │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  ┌──────────────┐  ┌──────────────┐  ┌─────────────┐  │
│  │ Avatar API   │  │ MESSAGING    │  │ Holon       │  │
│  │ (Identity)   │  │ API          │  │ System      │  │
│  └──────────────┘  └──────────────┘  └─────────────┘  │
│                                                         │
│  ┌──────────────┐  ┌──────────────┐  ┌─────────────┐  │
│  │ HyperDrive   │  │ Provider     │  │ STATS API   │  │
│  │ (Consensus)  │  │ System       │  │ (Metrics)   │  │
│  └──────────────┘  └──────────────┘  └─────────────┘  │
│                                                         │
└─────────────────────────────────────────────────────────┘

Part 6: Example: Multi-Agent Image Generation Workflow

Use Case: Generate and analyze an image using multiple agents

// Step 1: Register agents
await oasis.agents.register({
  agentId: "text_agent",
  capabilities: [{ type: "text_analysis" }]
});

await oasis.agents.register({
  agentId: "image_agent",
  capabilities: [{ type: "image_generation" }]
});

await oasis.agents.register({
  agentId: "analysis_agent",
  capabilities: [{ type: "image_analysis" }]
});

// Step 2: Create workflow
const workflow = await oasis.agents.workflows.create({
  workflowId: "image_gen_workflow",
  steps: [
    {
      stepId: "analyze_text",
      type: "text_analysis",
      agent: "text_agent", // or auto-discover
      input: "{{input.text}}"
    },
    {
      stepId: "generate_image",
      type: "image_generation",
      agent: "image_agent",
      input: "{{analyze_text.result.summary}}",
      dependsOn: ["analyze_text"]
    },
    {
      stepId: "analyze_image",
      type: "image_analysis",
      agent: "analysis_agent",
      input: "{{generate_image.result.imageUrl}}",
      dependsOn: ["generate_image"]
    }
  ]
});

// Step 3: Execute workflow
const result = await oasis.agents.workflows.execute({
  workflowId: "image_gen_workflow",
  input: {
    text: "A futuristic cityscape at sunset"
  }
});

// Step 4: Get results
// result.steps.analyze_text.result = { summary: "..." }
// result.steps.generate_image.result = { imageUrl: "..." }
// result.steps.analyze_image.result = { description: "..." }

What OASIS Provides:

✅ Agent identity (Avatar API)
✅ Agent communication (MESSAGING API)
✅ Shared state (Holon system)
✅ Task routing (HyperDrive)
✅ Persistence (Multi-provider)
✅ Consensus (HyperDrive engine)

What We Need to Build:

🚧 Agent registry/discovery
🚧 Task queue system
🚧 Workflow engine
🚧 Agent monitoring

Part 7: Competitive Advantages

Why OASIS is Perfect for AI Agents:

Multi-Chain by Default
- Agents can operate across 50+ blockchains
- No single point of failure
- Cross-chain agent state
Proven Reliability
- 4+ years production experience
- Auto-failover ensures uptime
- Enterprise-grade infrastructure
Complete Infrastructure
- Identity, messaging, storage, consensus all built
- Just need agent-specific orchestration layer
Cost-Effective
- One API replaces entire agent infrastructure
- No need to build from scratch
Future-Proof
- New providers = new agent capabilities automatically
- Universal API works with any agent framework

Part 8: Success Metrics

Key Performance Indicators:

Agent Registration
- Target: 1000+ agents registered in first 6 months
- Metric: Agents registered per week
Task Throughput
- Target: 1M+ tasks processed per month
- Metric: Tasks per second
Agent Uptime
- Target: 99.9% agent availability
- Metric: Agent health monitoring
Workflow Success Rate
- Target: 95%+ workflow completion rate
- Metric: Successful workflows / total workflows
Agent Discovery
- Target: <100ms agent discovery time
- Metric: Discovery API response time

Conclusion

OASIS provides 60% of what AI agents need through existing infrastructure. We need to build 4 new layers (Agent Registry, Task Queue, Workflow Engine, Monitoring) to complete the agent orchestration platform.

Timeline: 6 months to full agent platform Priority: High - This is a major market opportunity Complexity: Medium - Building on solid foundation

Next Steps:

Start Phase 1 (Agent Registry) immediately
Partner with AI agent frameworks (LangChain, AutoGPT)
Build MVP in 6 weeks
Launch beta with select partners

Created: January 2026 Status: Ready for Implementation Contact: For questions about agent requirements

PreviousYC Startup Ideas Response NextOpenServ × OASIS Integration

Last updated 12 days ago

Good evening

What AI Agents Need to Be Successful

Executive Summary

Part 1: What AI Agents Need (The 10 Core Requirements)

1. Identity & Discovery 🔑

2. Communication & Messaging 💬

3. Shared State & Memory 🧠

4. Task Delegation & Routing 📋

5. Resource Management 💻

6. Security & Permissions 🔒

7. Observability & Debugging 🔍

8. Consensus & Coordination 🤝

9. Persistence & Reliability 💾

10. Workflow Orchestration 🔄

Part 2: What OASIS Already Provides (The Foundation)

✅ Already Built - Ready to Use:

1. Identity System (Avatar API)

2. Communication (MESSAGING API)

3. Shared State (Holon System)

4. Resource Management (Provider System)

5. Consensus Engine (HyperDrive)

6. Observability (STATS API)

Part 3: What We Need to Build (The Agent Layer)

🚧 New Capabilities Required:

1. Agent Registry & Discovery System ⭐ HIGH PRIORITY

2. Task Queue & Workflow Engine ⭐ HIGH PRIORITY

3. Agent Communication Protocol ⭐ MEDIUM PRIORITY

4. Agent Monitoring & Debugging Dashboard ⭐ MEDIUM PRIORITY

Part 4: Implementation Roadmap

Phase 1: Foundation (Weeks 1-6) ⭐ CRITICAL

Phase 2: Communication (Weeks 7-12) ⭐ HIGH PRIORITY

Phase 3: Orchestration (Weeks 13-18) ⭐ HIGH PRIORITY

Phase 4: Observability (Weeks 19-24) ⭐ MEDIUM PRIORITY

Part 5: Technical Architecture

Agent Layer Architecture

Part 6: Example: Multi-Agent Image Generation Workflow

Use Case: Generate and analyze an image using multiple agents

Part 7: Competitive Advantages

Why OASIS is Perfect for AI Agents:

Part 8: Success Metrics

Key Performance Indicators:

Conclusion